Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data

Qingjie Liu; Xiaoyan Lei; Jerry G. Rose; Qingsong Feng; Teng Wang

doi:10.12783/shm2019/32163

Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data

Qingjie Liu
, Xiaoyan Lei
, Jerry G. Rose
, Qingsong Feng
, Teng Wang

Kentucky Transportation Center (KTC)

Producción científica: Conference contribution › revisión exhaustiva

Resumen

A Model-Based Estimate Method (MBEM) was introduced to estimate wheel-rail force by using track dynamic response data, the estimated result then be used for of OOR wheels identification. The function of dynamic force transfer between the wheel-rail force and tie displacement was developed based on a double layers track model. A case study was conducted to verify the result. Test equipment was made for tie-ballast interface pressure measurement. The equipment was installed on a heavy-haul railway line in the United States, long-term monitoring on ballast pressure was conducted. A series of preprocessing methods were used to obtain the normalized pressure data. According to the comparison between Wheel Impact Load Detector (WILD) data and ballast pressure data, the relationship between ballast pressure and wheel load was established. The wheel-rail force of each wheel was calculated by using the MBEM method.

Idioma original	English
Título de la publicación alojada	Structural Health Monitoring 2019
Subtítulo de la publicación alojada	Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
Editores	Fu-Kuo Chang, Alfredo Guemes, Fotis Kopsaftopoulos
Páginas	585-594
Número de páginas	10
ISBN (versión digital)	9781605956015
DOI	https://doi.org/10.12783/shm2019/32163
Estado	Published - 2019
Evento	12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 - Stanford, United States Duración: sept 10 2019 → sept 12 2019

Serie de la publicación

Nombre	Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
Volumen	1

Conference

Conference	12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
País/Territorio	United States
Ciudad	Stanford
Período	9/10/19 → 9/12/19

Nota bibliográfica

Funding Information:
This research was supported by the Chinese National Natural Science Foundation (51868024) and the National University Rail Center (NURail), a U.S. DOT OST Tier 1 University Transportation Center. Special appreciation is extended to Norfolk Southern Railway for providing the track test site and arranging the logistics and assistance associated with the in-track tests. Also, LB Foster (Salient Systems) Company assisted with the WILD data exportation and data processing techniques.

Publisher Copyright:
© International Workshop on Structural Health Monitoring. All rights reserved.

Financiación

This research was supported by the Chinese National Natural Science Foundation (51868024) and the National University Rail Center (NURail), a U.S. DOT OST Tier 1 University Transportation Center. Special appreciation is extended to Norfolk Southern Railway for providing the track test site and arranging the logistics and assistance associated with the in-track tests. Also, LB Foster (Salient Systems) Company assisted with the WILD data exportation and data processing techniques.

Financiadores	Número del financiador
National University Rail Center
U.S. DOT OST Tier 1 University Transportation Center
National Natural Science Foundation of China (NSFC)	51868024

ASJC Scopus subject areas

Computer Science Applications
Health Information Management

Acceder al documento

10.12783/shm2019/32163

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Citar esto

Liu, Q., Lei, X., Rose, J. G., Feng, Q., & Wang, T. (2019). Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data. En F.-K. Chang, A. Guemes, & F. Kopsaftopoulos (Eds.), Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring (pp. 585-594). (Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring; Vol. 1). https://doi.org/10.12783/shm2019/32163

Liu, Qingjie ; Lei, Xiaoyan ; Rose, Jerry G. et al. / Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data. Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring. editor / Fu-Kuo Chang ; Alfredo Guemes ; Fotis Kopsaftopoulos. 2019. pp. 585-594 (Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring).

@inproceedings{2f625462c71544f9aeef701a0889eb56,

title = "Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data",

abstract = "A Model-Based Estimate Method (MBEM) was introduced to estimate wheel-rail force by using track dynamic response data, the estimated result then be used for of OOR wheels identification. The function of dynamic force transfer between the wheel-rail force and tie displacement was developed based on a double layers track model. A case study was conducted to verify the result. Test equipment was made for tie-ballast interface pressure measurement. The equipment was installed on a heavy-haul railway line in the United States, long-term monitoring on ballast pressure was conducted. A series of preprocessing methods were used to obtain the normalized pressure data. According to the comparison between Wheel Impact Load Detector (WILD) data and ballast pressure data, the relationship between ballast pressure and wheel load was established. The wheel-rail force of each wheel was calculated by using the MBEM method.",

author = "Qingjie Liu and Xiaoyan Lei and Rose, \{Jerry G.\} and Qingsong Feng and Teng Wang",

note = "Funding Information: This research was supported by the Chinese National Natural Science Foundation (51868024) and the National University Rail Center (NURail), a U.S. DOT OST Tier 1 University Transportation Center. Special appreciation is extended to Norfolk Southern Railway for providing the track test site and arranging the logistics and assistance associated with the in-track tests. Also, LB Foster (Salient Systems) Company assisted with the WILD data exportation and data processing techniques. Publisher Copyright: {\textcopyright} International Workshop on Structural Health Monitoring. All rights reserved.; 12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 ; Conference date: 10-09-2019 Through 12-09-2019",

year = "2019",

doi = "10.12783/shm2019/32163",

language = "English",

series = "Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring",

pages = "585--594",

editor = "Fu-Kuo Chang and Alfredo Guemes and Fotis Kopsaftopoulos",

booktitle = "Structural Health Monitoring 2019",

}

Liu, Q, Lei, X, Rose, JG, Feng, Q & Wang, T 2019, Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data. En F-K Chang, A Guemes & F Kopsaftopoulos (eds.), Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring. Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring, vol. 1, pp. 585-594, 12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019, Stanford, United States, 9/10/19. https://doi.org/10.12783/shm2019/32163

Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data. / Liu, Qingjie; Lei, Xiaoyan; Rose, Jerry G. et al.
Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring. ed. / Fu-Kuo Chang; Alfredo Guemes; Fotis Kopsaftopoulos. 2019. p. 585-594 (Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring; Vol. 1).

Producción científica: Conference contribution › revisión exhaustiva

TY - GEN

T1 - Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data

AU - Liu, Qingjie

AU - Lei, Xiaoyan

AU - Rose, Jerry G.

AU - Feng, Qingsong

AU - Wang, Teng

N1 - Funding Information: This research was supported by the Chinese National Natural Science Foundation (51868024) and the National University Rail Center (NURail), a U.S. DOT OST Tier 1 University Transportation Center. Special appreciation is extended to Norfolk Southern Railway for providing the track test site and arranging the logistics and assistance associated with the in-track tests. Also, LB Foster (Salient Systems) Company assisted with the WILD data exportation and data processing techniques. Publisher Copyright: © International Workshop on Structural Health Monitoring. All rights reserved.

PY - 2019

Y1 - 2019

N2 - A Model-Based Estimate Method (MBEM) was introduced to estimate wheel-rail force by using track dynamic response data, the estimated result then be used for of OOR wheels identification. The function of dynamic force transfer between the wheel-rail force and tie displacement was developed based on a double layers track model. A case study was conducted to verify the result. Test equipment was made for tie-ballast interface pressure measurement. The equipment was installed on a heavy-haul railway line in the United States, long-term monitoring on ballast pressure was conducted. A series of preprocessing methods were used to obtain the normalized pressure data. According to the comparison between Wheel Impact Load Detector (WILD) data and ballast pressure data, the relationship between ballast pressure and wheel load was established. The wheel-rail force of each wheel was calculated by using the MBEM method.

AB - A Model-Based Estimate Method (MBEM) was introduced to estimate wheel-rail force by using track dynamic response data, the estimated result then be used for of OOR wheels identification. The function of dynamic force transfer between the wheel-rail force and tie displacement was developed based on a double layers track model. A case study was conducted to verify the result. Test equipment was made for tie-ballast interface pressure measurement. The equipment was installed on a heavy-haul railway line in the United States, long-term monitoring on ballast pressure was conducted. A series of preprocessing methods were used to obtain the normalized pressure data. According to the comparison between Wheel Impact Load Detector (WILD) data and ballast pressure data, the relationship between ballast pressure and wheel load was established. The wheel-rail force of each wheel was calculated by using the MBEM method.

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DO - 10.12783/shm2019/32163

M3 - Conference contribution

AN - SCOPUS:85074424371

T3 - Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring

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BT - Structural Health Monitoring 2019

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Liu Q, Lei X, Rose JG, Feng Q, Wang T. Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data. En Chang FK, Guemes A, Kopsaftopoulos F, editores, Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring. 2019. p. 585-594. (Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring). doi: 10.12783/shm2019/32163

Identification of out-of-round wheels on heavy-haul railway lines by using ballast pressure data

Resumen

Serie de la publicación

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Nota bibliográfica

Financiación

ASJC Scopus subject areas

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